app.py

import gradio as gr
from transformers import pipeline

classifier = pipeline(
    "sentiment-analysis",
    model="distilbert/distilbert-base-uncased-finetuned-sst-2-english",
    device=-1,
)

def classify_sentiment(text: str):
    if not text or not text.strip():
        return {"error": "No text provided"}
    # No top_k — returns flat list [{"label": ..., "score": ...}, ...]
    results = classifier(text, truncation=True, max_length=512)
    return [
        {"label": r["label"], "score": round(r["score"], 4)}
        for r in results
    ]

demo = gr.Interface(
    fn=classify_sentiment,
    inputs=gr.Textbox(label="Article Text"),
    outputs=gr.JSON(label="Sentiment Classification"),
    title="Sentiment Classifier",
)

demo.launch(ssr_mode=False)